Search Results - (( using classification modified algorithm ) OR ( basic optimization learning algorithm ))
Search alternatives:
- classification modified »
- optimization learning »
- using classification »
- basic optimization »
- learning algorithm »
-
1
Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome
Published 2014“…In the development of the “hybrid AI-based” classification models, the proposed model (K1-K2- NN), was basically introduced through combining AI approaches of modified K-NN, genetic algorithm (GA), Fisher’s discriminant ratio (FDR) and class separability criteria (CSC). …”
Get full text
Get full text
Get full text
Thesis -
2
Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
Get full text
Get full text
Get full text
Article -
3
The use of SOM for fingerprint classification
Published 2023“…This paper introduces an approach to fingerprint classification by using Self-Organizing Maps (SOM). In order to be able to deal with fingerprint images having distorted regions, the SOM learning and classification algorithms are modified. …”
Conference paper -
4
A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. …”
Get full text
Get full text
Get full text
Article -
5
Modified word representation vector based scalar weight for contextual text classification
Published 2024“…In addition, a contextual text classification experiment is conducted using benchmarked datasets to assess the performance of the modified word vectors in the targeted classification task. …”
Get full text
Get full text
Thesis -
6
A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification
Published 2010“…The first stage consists of a modified fuzzy min-max (FMM) neural-network-based pattern classifier, while the second stage consists of a genetic-algorithm (GA)-based rule extractor. …”
Get full text
Article -
7
Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…The single layer property of FLNN also make the learning algorithm used less complicated compared to MLP network. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
8
Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
Get full text
Get full text
Conference or Workshop Item -
9
A hybrid-based modified adaptive fuzzy inference engine for pattern classification
Published 2011“…A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data set. …”
Get full text
Get full text
Conference or Workshop Item -
10
An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2013“…In this paper, a modified Artificial Bee Colony (mABC) is used to recover the BP drawbacks. …”
Get full text
Get full text
Get full text
Article -
11
An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…In this paper, a modified Artificial Bee Colony (mABC) is used to recover the BP drawbacks. …”
Get full text
Get full text
Article -
12
An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…In this paper, a modified Artificial Bee Colony (mABC) is used to recover the BP drawbacks. …”
Get full text
Get full text
Article -
13
Comparison between Lamarckian Evolution and Baldwin Evolution of neural network
Published 2006“…Hybrid genetic algorithms are the combination of learning algorithms(Back propagation), usually working as evaluation functions, and genetic algorithms. …”
Get full text
Get full text
Get full text
Article -
14
Modified anfis architecture with less computational complexities for classification problems
Published 2018“…The results show that the proposed modified ANFIS architecture with gaussian membership function and Artificial Bee Colony (ABC) optimization algorithm, on average has achieved classification accuracy of 99.5% with 83% less computational complexity.…”
Get full text
Get full text
Get full text
Get full text
Thesis -
15
An Improved Wavelet Neural Network For Classification And Function Approximation
Published 2011“…The modified WNN was then applied in the areas of classification and function approximation.…”
Get full text
Get full text
Thesis -
16
Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
Get full text
Get full text
Thesis -
17
The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification
Published 2020“…However, none of the available works had proposed BFOA as a classification algorithm despite of its good performance. …”
Get full text
Get full text
Get full text
Thesis -
18
Reliable multiclass cancer classification of microarray gene expression profiles using an improved wavelet neural network
Published 2011“…The modified WNN was then applied to heterogeneous cancer classification using four different microarray benchmark datasets. …”
Get full text
Get full text
Get full text
Article -
19
Automated classification of blasts in acute leukemia blood samples using HMLP network
Published 2011“…This paper presents a study on classification of blasts in acute leukemia blood samples using artificial neural network.In acute leukemia there are two major forms that are acute myelogenous leukemia (AML) and acute lymphocytic leukemia (ALL).Six morphological features have been extracted from acute leukemia blood images and used as neural network inputs for the classification.Hybrid Multilayer Perceptron (HMLP) neural network was used to perform the classification task.The Hybrid Multilayer Perceptron(HMLP) neural network is trained using modified RPE(MRPE) training algorithm for 1474 data samples.The Hybrid Multilayer Perceptron (HMLP) neural network produces 97.04% performance accuracy.The result indicates the promising capabilities and abilities of the Hybrid Multilayer Perceptron (HMLP) neural network using modified RPE (MRPE) training algorithm for classifying and distinguishing the blasts from acute leukemia blood samples.…”
Get full text
Get full text
Get full text
Conference or Workshop Item -
20
A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system
Published 2018“…This work proposes the extreme learning machine (ELM) is one of the poplar machine learning algorithms which, easy to implement with excellent learning performance characteristics. …”
Get full text
Get full text
Get full text
Conference or Workshop Item
